The current lack of diversity in genomic research data is hindering what we can learn about health and potential treatments in our global population. By enhancing the diversity of people participating in genomic research, we can advance our knowledge and discovery of human genetics for all populations. To that end, The Charles Bronfman Institute for Personalized Medicine is spearheading the effort to carry out the genetic sequencing of one million Mount Sinai patients within the next five years. This initiative, one of the largest such sequencing projects of its kind, will integrate health and research data at Mount Sinai to promote discoveries that will directly benefit our patient population.
Called the Mount Sinai Million Health Discoveries Program, this initiative is seen as a model for building genetics into the real world of clinical care. The wealth of knowledge derived directly from one of the world’s most diverse patient populations, as available within a massive New York City health system, will improve our understanding about the connection between genetics and disease. This program will potentially provide insights into every disease area and will have a tremendous impact on the future of science and medicine.
We anticipate a wide range of critical discoveries, from novel therapeutics to treat, cure, and ultimately prevent disease to a newfound understanding of what health itself means at the genetic level. Importantly, because of the ethnic and racial diversity of Mount Sinai’s patients, Mount Sinai Million will also dramatically expand our knowledge of the biological basis of all common diseases that affect people across the globe. The Mount Sinai Million program will mark the first time a health system of this size and diversity has integrated genomic profiling into routine clinical decision-making to understand the impact of genetic variations on human health and disease.
To enroll as a participant or to learn more about the Mount Sinai Million Health Discoveries Program, visit mountsinaimillion.org.